Title :
Invexity of the Minimum Error Entropy Criterion
Author :
Syed, M. ; Pardalos, Panos ; Principe, Jose
Author_Institution :
Dept. of Ind. & Syst. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
In this letter, optimization properties of Minimization of Error Entropy (MEE) and Minimization of Error Entropy with Fiducial points (MEEF) are presented. It is proved that by varying the kernel parameter of the MEE and/or MEEF objective function, the resulting problem, in general leads to an invex problem. Furthermore, for certain values of the kernel parameter it is shown that the problems may transform to convex or pseudo-convex problems.
Keywords :
convex programming; entropy; minimisation; MEEF; invex problem; kernel parameter; minimization of error entropy with fiducial points; minimum error entropy criterion invexity; optimization properties; pseudo convex problems; Entropy; Kernel; Measurement uncertainty; Minimization; Optimization; Robustness; Signal processing algorithms; Entropic learning; error entropy; information potential; information theoretic learning;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2013.2283425
